The user can select a sample of interest and perform curve fitting using a single or double term exponential equation. The T-half (half maximal recovery time) and Mobile Fraction values (individual and mean values) are computed. The actual data, fitted curve and the residuals are visualized in order to evaluate the fit. Goodness-of-fit statistics (R2) are also provided. More specifically, the program returns the value of R-square, which is the square of the correlation between the response values and the predicted response values. For a detailed presentation of the fitting process, see the easyfrap manual appendix.
To perform curve fitting, the user must select the appropriate equation and press the Perform Curve Fitting button of the corresponding file. The mobile fraction, half-time of immobilization and R square of the fitting are displayed, as well as the fitted curve and fitting residuals. Graphs can be easily exported as .png images by pressing the SAVE GRAPHS button. To perform curve fitting for the average values of the selected files, the user must press the FIT MEAN DATA button. Please note that fitting a mean curve is not the same as fitting individual curves and obtaining a mean of the computed parameters. The Fit Mean functionality should only be used as a rough estimate of protein kinetics, as it cannot depict cell-to-cell heterogeneity, which is important for interpreting biological behavior.
To analyze several individual curves simultaneously, the user must press the SAVE RESULTS button. The user is prompted to select the individual curves of interest and save the final fitting results (R-square, T-half, Mobile Fraction for every individual curve and their mean values/standard deviation) in a separate .xlsx file. At the same time, data for fitted curves (both the experimental and fitted intensities) as well as fitting residuals for each curve analyzed are exported in a second sheet of the same .xlsx file for further use.
It should be noted that the uploaded datasets will not be stored on the server after the end of the analysis. Periodically, all the old records are automatically deleted in order for the system to be maintained at a high performance level. Additionally, the user is able to manually delete the uploaded data after finishing the analysis by pressing the DELETE THE ENTIRE DATASET button.
Finally, data removal is also triggered when the RESET ALL button of the Dataset Selection panel is pressed.